Writer identification in old music manuscripts using Contour-Hinge feature and dimensionality reduction with an autoencoder

Although most of the previous studies in writer identification in music scores assumed successful prior staff-line removal, this assumption does not hold when the music scores suffer from a certain level of degradation or deformation. The impact of staff-line removal on the result of writer identification in such documents is rather vague. In this study, we propose a novel writer identification method that requires no staff-line removal and no segmentation. Staff-line removal is virtually achieved without image processing, by dimensionality reduction with an autoencoder in Contour-Hinge feature space. The experimental result with a wide range of music manuscripts shows the proposed method can achieve favourable results without prior staff-line removal.